Population size and differential population growth of introduced Greater Canada Geese<i>Branta canadensis</i>and re-established Greylag Geese<i>Anser anser</i>across habitats in Great Britain in the year 2000
Bibliographic record
Abstract
Capsule Both populations are increasing at a similar rate. Aims During 2000, an extensive survey of introduced Greater Canada Geese and re-established Greylag Geese in Great Britain was undertaken in order to update population estimates last made between 1988 and 1991. Methods A randomized stratified sample of 1329 of the 61 510 tetrads (2 km × 2 km unit) in Great Britain was surveyed. The habitat categories, or strata, were based on the proportion of water cover, urbanization, and upland/lowland in each tetrad. Non-urbanized strata were further divided into northern and southern reporting areas. Results In 2000 there were an estimated 88 866 full-grown Greater Canada Geese and 24 522 full-grown Greylag Geese in Great Britain. Since the 1988–91 survey, Greater Canada Geese have increased by 166% and Greylag Geese by 170%, an average per annum rate of increase of 9.3% for Greater Canada Geese and 9.4% for Greylag Geese. The increase in Greater Canada Goose numbers since the 1988–91 survey has occurred mainly in habitats which had previously held low goose population densities, particularly the ‘no water’ lowland habitat. Although densities were still relatively low in this habitat (<0.5 geese per km2), because of its extent it supported 56% of the total Greater Canada Goose population in 2000. The greatest increase in re-established Greylag Goose numbers has arisen from an expansion into lowland habitat with some water cover. Conclusion There was no obvious decline in the 8.3% per annum Greater Canada Goose growth rate that caused the population to treble between 1976 and 1991. Greylag Goose numbers are increasing at a similar rate to those of the Greater Canada Goose.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".